Remote patient monitoring using artificial intelligence: Current state, applications, and challenges
The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
Machine learning techniques in adaptive and personalized systems for health and wellness
Traditional health systems mostly rely on rules created by experts to offer adaptive
interventions to patients. However, with recent advances in artificial intelligence (AI) and …
interventions to patients. However, with recent advances in artificial intelligence (AI) and …
Voting-based decentralized consensus design for improving the efficiency and security of consortium blockchain
Since its emergence, blockchain technology has received great attention because of its
advantages in terms of decentralization, transparency, traceability, and the ability to be …
advantages in terms of decentralization, transparency, traceability, and the ability to be …
A systematic review of machine learning and IoT applied to the prediction and monitoring of cardiovascular diseases
According to the Pan American Health Organization, cardiovascular disease is the leading
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
Survey of deep learning techniques for disease prediction based on omics data
X Yu, S Zhou, H Zou, Q Wang, C Liu, M Zang, T Liu - Human Gene, 2023 - Elsevier
In the era of big data, computer science has been applied to every aspect of biomedical
field. At the same time, transforming biomedical data into valuable knowledge is one of the …
field. At the same time, transforming biomedical data into valuable knowledge is one of the …
Efficient and traceable patient health data search system for hospital management in smart cities
Smart city, as a new mode, is introduced to improve the level of city management for modern
cities. In smart cities, a kernel field is health management for urban residents. Hospital …
cities. In smart cities, a kernel field is health management for urban residents. Hospital …
Machine learning in radar-based physiological signals sensing: a sco** review of the models, datasets and metrics
In the field of physiological signals monitoring and its applications, non-contact technology is
often proposed as a possible alternative to traditional contact devices. The ability to extract …
often proposed as a possible alternative to traditional contact devices. The ability to extract …
[PDF][PDF] Software for Statistical Processing and Modeling of a Set of Synchronously Registered Cardio Signals of Different Physical Nature.
It has been developed the software complex, that allows to perform mutual statistical
processing of synchronously registered cardiosignals on the basis of the vector model of the …
processing of synchronously registered cardiosignals on the basis of the vector model of the …
Ensemble classification technique for heart disease prediction with meta-heuristic-enabled training system
Objectives This research work exclusively aims to develop a novel heart disease prediction
framework including three major phases, namely proposed feature extraction …
framework including three major phases, namely proposed feature extraction …
[HTML][HTML] Deep-learning-based real-time passive non-line-of-sight imaging for room-scale scenes
Y Li, Y Zhang - Sensors, 2024 - mdpi.com
Non-line-of-sight imaging is a technique for reconstructing scenes behind obstacles. We
report a real-time passive non-line-of-sight (NLOS) imaging method for room-scale hidden …
report a real-time passive non-line-of-sight (NLOS) imaging method for room-scale hidden …